Modelling co-designed geoprospective scenarios to assess greening adaptation strategies at the metropolitan scale

In the context of climate change, it is crucial to develop methods for assessing the impact of green infrastructures on urban climates through a co-constructive process with local planners. The study proposes a methodological framework for modelling geoprospective greening scenarios in collaboration with the metropolitan services of Dijon (eastern France, 260 000 inhabitants).

A sensitivity analysis confirms the suitability of the Town Energy Balance (TEB) model coupled with Méso-NH for simulating the effects of tall and short vegetation on the UHI. It also highlights the need for detailed vegetation databases to ensure research remains aligned with local conditions, which is especially important in action research.

The collaborative development of vegetation scenarios is anchored in the theoretical framework of geoprospective. This approach yields contrasting scenarios tailored to local contexts and leads to realistic greening guidelines derived from urban planning documents. These scenarios address a wide range of concerns raised by local planners, validating geoprospective as an effective tool for informing institutional decision-making. One scenario in particular stands out: it prioritizes the greening of available spaces in the city. It leads to add more than 100 000 trees and the equivalent of 4000 football fields. A dedicated QGIS plug-in was developed to support this scenario, paving the way for broader applications of scenario-based planning tools.

This scenario focuses largely on greening private gardens and commercial/industrial areas. Results shows a reduction of the intensity (by a mean of 2°C) and spatial extent of UHI, prompting further consideration of the role of private garden greening.

Overall, these findings highlight the need for an interdisciplinary methodological framework that integrates land-use planning, geomatics, and climate modelling. They also underscore the importance of combining action research with the translation of urban planning documents into scenarios, a strategy that could ultimately lead to the development of robust decision-support and urban planning tools.